Typically, image sensors are manufactured within a certain tolerance specification in which a few pixels have somewhat undesirable characteristics. These pixels are commonly referred to as “defective pixels” because, although they are operational, they do not have the same desired performance characteristics as the other pixels. Given a sufficiently low density, these defective pixels do not substantially degrade the quality of a captured image because they are typically replaced by calculated substitute values, which closely approximate the value if the pixel was not defective.
One such technique is to replace the defective pixel value with the average of a predetermined number of nearest neighbor values. This predetermined number of nearest neighbor could be two immediate adjacent pixels or four immediate adjacent pixels.
It is also instructive to note that image sensors are also formed from an array of identical cells (typically four immediate adjacent pixels) so that the imaging characteristics of the sensor are substantially uniform across the array. Design of these cells are often a trade-off or compromise of several competing imaging performance parameters, such as read-out rate, photosensitivity, and photo-response non-uniformity.
Consequently, a technique or method is needed to provide improvements in a specific imaging performance parameter without substantial degradation of other aspects. One such improvement is to use the knowledge that defective pixels do not substantially degrade image quality for enhancing other imaging parameters.